{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PyTorch Tutoria: 02 Dataset and Iterator\n",
    "## Overview \n",
    "In this tutorial, we will cover the basics of constructing dataset and iterators so that we can train models using gradient descent. \n",
    "\n",
    "The best tutorial can be found in the official website (https://pytorch.org/tutorials/beginner/data_loading_tutorial.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from torch.utils.data import Dataset, DataLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MyStupidDataset(Dataset):\n",
    "    def __init__(self):\n",
    "        super(MyStupidDataset, self).__init__()\n",
    "        self.data = torch.randn([1024, 10, 10])\n",
    "    def __len__(self):\n",
    "        return 1024\n",
    "    def __getitem__(self, idx):\n",
    "        return self.data[idx, :, :] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_stupid_dataset = MyStupidDataset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_data_loader = DataLoader(my_stupid_dataset, batch_size=64, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "         [-1.0649,  0.0584, -0.9167,  ...,  1.1136, -0.3728,  0.4191],\n",
      "         [ 0.5729, -1.2280, -0.5642,  ...,  1.6796,  0.1244, -0.2625],\n",
      "         ...,\n",
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      "\n",
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      "         ...,\n",
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      "\n",
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      "         ...,\n",
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      "\n",
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      "\n",
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      "         [ 0.2934,  1.7401,  1.4920,  ..., -0.6745, -0.2860,  0.0657]]])\n",
      "tensor([[[-5.6312e-01, -1.2491e+00, -8.6892e-02,  ..., -5.5828e-01,\n",
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      "\n",
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      "\n",
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      "\n",
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      "           1.6161e+00, -6.5070e-01]],\n",
      "\n",
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      "\n",
      "        [[ 4.0593e-01, -1.6476e+00, -1.6729e-01,  ..., -2.6257e-01,\n",
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      "          -1.1135e+00, -1.0044e+00]]])\n",
      "tensor([[[ 1.6199e+00, -1.0639e-01, -5.3365e-01,  ...,  5.6152e-01,\n",
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      "\n",
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      "\n",
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      "         ...,\n",
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      "           1.5137e+00, -4.7078e-01]],\n",
      "\n",
      "        ...,\n",
      "\n",
      "        [[-5.7024e-01,  2.9021e+00,  9.7182e-01,  ...,  3.7831e-01,\n",
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      "         ...,\n",
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      "\n",
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      "         ...,\n",
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      "           8.6611e-01, -9.6669e-01],\n",
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      "          -1.6173e+00, -9.9486e-02]],\n",
      "\n",
      "        [[-7.4066e-01, -2.3019e-01, -1.0080e+00,  ...,  3.0344e-01,\n",
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      "         ...,\n",
      "         [ 6.1342e-01, -1.0359e-01, -1.8878e-01,  ..., -1.1351e+00,\n",
      "          -7.2189e-01, -1.5223e+00],\n",
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      "           8.1821e-01, -1.3640e+00]]])\n",
      "tensor([[[-1.3117, -0.8945,  0.7644,  ..., -0.2785, -1.2176,  0.0159],\n",
      "         [ 1.6932,  0.6903,  0.4031,  ..., -1.5412,  0.5249,  1.8902],\n",
      "         [-1.0512, -0.3552,  0.8488,  ..., -0.2282,  1.7660,  1.4979],\n",
      "         ...,\n",
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      "         [-0.0681,  0.8428, -0.4261,  ...,  0.2989,  0.1486, -2.5058]],\n",
      "\n",
      "        [[-0.7508,  0.2202, -0.4306,  ...,  0.4052, -1.2458,  0.8271],\n",
      "         [-0.8011,  0.0911, -0.9894,  ..., -1.2840, -0.5898,  0.0091],\n",
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      "         ...,\n",
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      "\n",
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      "         [ 0.3698, -0.1131,  0.6544,  ..., -0.4409, -2.7405, -2.4045]]])\n",
      "tensor([[[ 1.2119, -1.0708,  0.5649,  ..., -0.4971,  1.0620,  0.7310],\n",
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      "\n",
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      "\n",
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      "         [-0.3274, -0.2323, -0.9700,  ..., -0.7615, -0.1325,  1.0422]],\n",
      "\n",
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      "         [ 0.0841,  1.8605, -1.4453,  ...,  0.7873,  0.8140, -0.9502],\n",
      "         [ 1.2973,  0.3144,  0.3507,  ..., -0.6038,  0.6975, -0.3158]]])\n",
      "tensor([[[ 2.1653e+00,  1.4066e+00, -1.4018e-01,  ...,  1.1781e-01,\n",
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      "           1.5917e+00,  2.4525e-01]],\n",
      "\n",
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      "          -1.4771e+00, -2.4199e-01]],\n",
      "\n",
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      "\n",
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      "          -1.5118e+00, -1.2853e+00]],\n",
      "\n",
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      "          -1.7046e+00, -5.6116e-01]],\n",
      "\n",
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      "           7.6247e-01, -1.3544e+00]]])\n",
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      "\n",
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      "         [-0.6550,  0.1830,  0.8013,  ...,  1.3333, -1.8975, -1.8111]]])\n",
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      "\n",
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      "         [ 1.2054,  0.1532, -0.2913,  ...,  0.8937,  1.3827, -0.7586],\n",
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      "         ...,\n",
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      "         [-0.9593,  1.2607,  0.8724,  ..., -2.0466,  1.4395, -0.2859]],\n",
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      "\n",
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      "         [-1.3459, -0.5093,  0.3744,  ..., -1.1514, -1.8655, -0.4715],\n",
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      "         ...,\n",
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      "         [ 0.0484,  0.6638,  0.5932,  ...,  0.0103,  0.4403,  0.2038]]])\n",
      "tensor([[[-0.5001,  0.7655, -1.5892,  ...,  1.5173, -0.1889,  0.1969],\n",
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      "         [ 1.8579, -0.6235,  0.0711,  ..., -0.7243, -1.6536,  0.2214]],\n",
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      "\n",
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      "         ...,\n",
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      "         [-1.0195,  0.3469, -0.8716,  ..., -0.8167, -0.7435,  0.8883]],\n",
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      "         ...,\n",
      "         [ 1.6550,  0.5316, -1.0206,  ..., -0.9902,  0.5366, -1.4679],\n",
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      "         [ 1.1645,  1.6547,  0.4743,  ...,  0.5693, -0.5106, -0.4570]],\n",
      "\n",
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      "         [-0.2861, -1.4594, -0.0288,  ..., -0.7547, -1.1133, -1.8543],\n",
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      "         ...,\n",
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      "         [-0.7631, -0.6232, -1.3942,  ...,  1.6226,  1.0339, -0.8199],\n",
      "         [-1.5753,  1.7589,  0.3334,  ..., -1.0937, -0.6524, -1.1210]]])\n",
      "tensor([[[ 3.1092e-02, -2.1838e-01, -1.1496e+00,  ..., -1.8493e+00,\n",
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      "           1.6904e+00, -1.2913e+00],\n",
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      "         ...,\n",
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      "           2.1138e+00,  9.0854e-01],\n",
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      "         [-1.8746e-01, -1.4980e+00,  8.2626e-01,  ..., -3.3720e-01,\n",
      "           2.3046e-01,  9.4482e-01]],\n",
      "\n",
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      "         ...,\n",
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      "          -3.6637e-01, -3.3053e-02],\n",
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      "          -2.4255e-01,  1.6382e+00],\n",
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      "          -8.8783e-01, -5.5539e-01]],\n",
      "\n",
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      "          -1.3814e+00,  1.0483e+00],\n",
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      "         ...,\n",
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      "          -2.3054e+00, -1.0945e+00],\n",
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      "          -9.9969e-01, -1.1980e+00]],\n",
      "\n",
      "        ...,\n",
      "\n",
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      "         ...,\n",
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      "          -3.1381e-01,  1.2592e+00],\n",
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      "           3.6489e-03,  9.3781e-01]],\n",
      "\n",
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      "           4.8354e-01,  1.0507e+00],\n",
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      "          -1.9183e-01,  1.0837e+00],\n",
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      "          -1.2022e+00,  1.9958e-01],\n",
      "         ...,\n",
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      "          -2.8208e-02,  4.5338e-01],\n",
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      "          -4.8293e-01,  5.8139e-02]],\n",
      "\n",
      "        [[ 1.7704e+00,  1.5224e+00,  4.3944e-01,  ..., -6.1627e-01,\n",
      "           7.2037e-01, -6.4579e-02],\n",
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      "         ...,\n",
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      "          -6.2404e-01, -9.0550e-01]]])\n",
      "tensor([[[-1.7698e+00, -2.3511e-01, -8.7736e-01,  ...,  5.2191e-01,\n",
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      "          -1.2090e+00,  8.0664e-01],\n",
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      "         ...,\n",
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      "          -7.0208e-01, -1.8103e+00]],\n",
      "\n",
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      "          -3.6634e-01,  1.8216e+00],\n",
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      "         ...,\n",
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      "           2.1489e-01, -1.0146e-01]],\n",
      "\n",
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      "          -1.6886e-01,  2.5458e+00],\n",
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      "         ...,\n",
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      "          -1.1980e+00, -9.5682e-01]],\n",
      "\n",
      "        ...,\n",
      "\n",
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      "         ...,\n",
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      "          -1.6170e+00,  4.9746e-01]],\n",
      "\n",
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      "         ...,\n",
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      "           9.0130e-01,  3.0235e-01]],\n",
      "\n",
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      "          -1.5872e+00, -2.8445e-01],\n",
      "         ...,\n",
      "         [ 6.7066e-01, -8.5731e-01,  1.3599e+00,  ...,  5.2378e-01,\n",
      "          -1.3736e+00, -3.6045e-01],\n",
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      "          -1.5711e+00,  5.9253e-01]]])\n",
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      "         ...,\n",
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      "\n",
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      "         [ 1.6969,  0.2717, -0.7711,  ..., -1.0051, -1.5770,  1.2443]]])\n",
      "tensor([[[-2.9995e-01, -1.4863e+00, -5.1337e-01,  ...,  7.6324e-01,\n",
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      "          -3.6137e-01,  6.2421e-02]],\n",
      "\n",
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      "\n",
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      "\n",
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      "          -4.1800e-02,  7.3589e-01]],\n",
      "\n",
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      "          -1.0506e+00, -7.9732e-01]]])\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "           6.9445e-01, -5.0606e-01]]])\n",
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      "        [[ 0.1703, -0.7386, -0.7755,  ...,  0.9994,  1.2104,  0.4352],\n",
      "         [ 1.6403,  0.4061,  0.7456,  ...,  0.8558,  0.5229,  1.3412],\n",
      "         [-0.3858, -0.2029, -0.2211,  ...,  0.9275, -0.0418,  0.3835],\n",
      "         ...,\n",
      "         [-0.0530,  0.0084, -0.9486,  ..., -0.4269,  0.3688,  0.1409],\n",
      "         [ 0.4046,  0.8975, -0.5751,  ...,  1.1916, -0.7468,  1.1817],\n",
      "         [-0.1368, -0.1990, -1.6800,  ..., -0.0467,  0.8468,  0.9299]]])\n",
      "tensor([[[ 0.2339, -0.0545,  0.3462,  ...,  0.7844, -0.5697, -0.7754],\n",
      "         [-1.3696,  1.2482,  1.4444,  ..., -0.3385, -1.1153,  1.2561],\n",
      "         [ 1.1201,  0.1532, -1.5417,  ...,  1.9303, -1.1823, -1.9116],\n",
      "         ...,\n",
      "         [ 0.4130,  1.9024, -0.0839,  ..., -1.1251, -0.0133, -0.7059],\n",
      "         [ 0.5126,  0.6009, -0.3197,  ..., -1.2095,  0.1741,  0.9702],\n",
      "         [ 1.4704, -0.1837, -0.6811,  ..., -0.7820,  0.5105,  0.6184]],\n",
      "\n",
      "        [[ 2.5426,  0.0653, -2.2162,  ..., -1.3649,  0.9259, -0.7085],\n",
      "         [ 0.9260,  0.9250, -2.0586,  ..., -0.0216,  0.7989, -2.0058],\n",
      "         [-0.5013,  0.0106,  0.6247,  ...,  1.2795,  0.1038, -0.0957],\n",
      "         ...,\n",
      "         [ 0.3883, -0.1381, -2.0017,  ..., -2.3893, -0.5460, -2.5624],\n",
      "         [ 1.5629, -0.0436, -0.7407,  ...,  0.8585,  1.7302,  1.0910],\n",
      "         [-0.2727, -0.5187, -1.9917,  ...,  0.1815,  1.0818,  0.3013]],\n",
      "\n",
      "        [[-0.3314, -0.1765, -0.3465,  ..., -0.9443, -1.0407, -1.3792],\n",
      "         [-0.0062, -0.2647, -2.2709,  ..., -0.0389,  0.5076,  3.3378],\n",
      "         [ 0.6079,  0.4137, -0.8696,  ...,  0.9478, -1.1918, -0.0933],\n",
      "         ...,\n",
      "         [-0.4684,  0.2085, -0.0953,  ...,  0.7526,  0.7512,  0.6800],\n",
      "         [ 0.8572,  1.5184,  0.6867,  ..., -0.6828, -0.2557,  1.4476],\n",
      "         [-0.2013,  0.3083, -1.7146,  ...,  0.0553, -0.3473,  0.9109]],\n",
      "\n",
      "        ...,\n",
      "\n",
      "        [[-1.9430,  0.9340,  0.3136,  ..., -0.7921, -0.0137, -1.4762],\n",
      "         [ 0.8011, -0.0579,  0.3904,  ..., -0.9884, -1.3121,  1.3590],\n",
      "         [ 1.1371,  0.8839,  1.2700,  ...,  0.1042,  1.3633, -1.4109],\n",
      "         ...,\n",
      "         [ 1.1223,  0.5923, -0.4864,  ..., -1.2879, -0.8175,  2.2513],\n",
      "         [ 0.9533,  1.0719,  0.5850,  ..., -0.1118, -0.6916,  0.5156],\n",
      "         [-0.3121, -0.5524, -0.4470,  ...,  1.2252,  0.6455, -1.7281]],\n",
      "\n",
      "        [[-0.3497, -1.3506,  0.1194,  ..., -0.2431,  0.2228,  0.2372],\n",
      "         [-2.3505, -0.7759,  0.2719,  ...,  0.1249, -0.4043,  0.5624],\n",
      "         [-0.1937,  0.4889,  1.3234,  ..., -0.7895,  0.4420,  0.4140],\n",
      "         ...,\n",
      "         [ 1.4594, -1.6009,  0.0367,  ...,  2.1814, -0.0789, -1.1782],\n",
      "         [ 0.4291, -0.1025,  2.2084,  ..., -0.4223, -1.0602, -0.3429],\n",
      "         [ 0.8136,  1.0280, -1.5908,  ..., -0.8462, -0.1049, -0.8747]],\n",
      "\n",
      "        [[ 0.6926,  0.6637,  1.0646,  ..., -0.0499,  0.4162, -1.0998],\n",
      "         [-1.0218,  0.6438,  1.8764,  ...,  0.0421,  0.5219, -0.3591],\n",
      "         [ 3.0118,  0.3640, -2.6522,  ..., -0.1284, -0.7330, -0.4042],\n",
      "         ...,\n",
      "         [-0.8113,  1.4694, -1.1049,  ...,  1.7039,  0.0786, -0.3414],\n",
      "         [ 0.4140,  0.4380,  0.1927,  ...,  1.4282,  0.7847,  1.2382],\n",
      "         [ 1.4092,  0.1020, -1.0754,  ..., -1.8250, -0.5010,  0.9894]]])\n"
     ]
    }
   ],
   "source": [
    "for i in my_data_loader:\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A common Pattern\n",
    "class MyDictDataset(Dataset):\n",
    "    def __init__(self):\n",
    "        super(MyDictDataset, self).__init__()\n",
    "        self.x = torch.randn(1024, 10)\n",
    "        self.y = torch.randn(1024)\n",
    "    def __len__(self):\n",
    "        return 1024\n",
    "    def __getitem__(self, idx):\n",
    "        return {'x':self.x[idx,:],'y':self.y[idx]}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[ 9.8082e-01, -2.8023e-01, -1.2525e+00, -3.6965e-01,  1.8818e-01,\n",
      "         -1.6073e+00,  9.3212e-01, -6.9147e-01, -3.3545e-02,  2.2559e-01],\n",
      "        [-2.1869e+00,  4.7473e-01,  3.7868e-03, -4.0867e-01,  1.6978e+00,\n",
      "          2.4035e+00,  1.2119e+00,  1.6577e-01, -6.0310e-01, -2.3801e-01],\n",
      "        [ 1.0599e-02, -3.6531e-01, -6.1027e-01,  9.3681e-01, -1.5954e-01,\n",
      "          1.0503e+00,  2.0387e+00,  3.9710e-01, -1.1716e+00,  9.8480e-01],\n",
      "        [ 2.4740e-01,  2.1640e-01,  6.1070e-01, -5.7585e-01,  2.1275e+00,\n",
      "         -5.2992e-01, -4.9332e-01,  4.5006e-02,  4.5715e-02, -1.1354e+00],\n",
      "        [-1.1164e+00,  5.4933e-01,  1.8641e+00,  1.8800e+00, -2.9633e-01,\n",
      "          5.0617e-01, -8.1875e-02,  1.3482e+00,  1.6780e+00, -1.9506e-01],\n",
      "        [ 9.7563e-01,  6.3292e-02,  7.3559e-01,  1.1803e+00,  1.6200e+00,\n",
      "          3.4809e-01, -7.0261e-01, -9.4948e-01,  5.2532e-01,  7.3993e-01],\n",
      "        [-4.5824e-01, -2.0280e-01, -3.5606e-01,  2.2650e-02, -4.9376e-01,\n",
      "          2.2427e-02,  3.7425e-01,  9.4323e-01,  3.1584e-01,  1.6192e-01],\n",
      "        [-2.9484e-01,  1.3650e-01, -1.1845e+00, -5.3006e-01, -7.0015e-01,\n",
      "          1.0503e+00, -1.3319e-02,  8.7459e-02, -1.1976e+00,  4.9992e-01],\n",
      "        [-4.7200e-01,  1.0712e-01,  1.2882e+00,  8.7105e-01, -1.3796e+00,\n",
      "          8.5883e-01,  1.7610e-01, -2.9457e-01, -5.1932e-01,  8.3693e-01],\n",
      "        [-6.4719e-01, -8.5002e-01, -2.4548e+00, -7.1431e-01, -1.1782e+00,\n",
      "         -4.3599e-01, -6.5406e-01,  2.2073e-01,  5.6244e-02,  1.6484e+00],\n",
      "        [ 4.7347e-01, -3.6566e-02, -6.4557e-01, -1.2118e-01, -4.2116e-01,\n",
      "          6.0494e-01,  1.6896e-01,  3.9971e-01,  1.0259e+00, -1.6971e-01],\n",
      "        [ 1.1335e+00,  3.7652e-01, -1.2642e+00,  1.1501e+00,  4.3403e-01,\n",
      "          2.6114e-01, -1.1482e+00, -1.9546e-01, -1.2604e+00,  3.7994e-01],\n",
      "        [-8.7859e-01,  1.6299e+00, -1.0604e+00, -3.9378e-01,  1.5612e+00,\n",
      "         -6.0046e-01, -3.9201e-01, -1.5444e+00, -1.1222e+00, -1.0631e+00],\n",
      "        [ 1.4063e+00, -1.7586e-01, -1.7079e+00,  9.4070e-02,  2.1236e+00,\n",
      "          2.3362e-01,  8.6987e-02, -1.3008e+00, -1.0034e+00, -1.1340e+00],\n",
      "        [-8.7563e-01,  4.9334e-01, -7.3514e-01, -1.4347e+00, -3.4856e-01,\n",
      "         -8.9019e-01, -2.0167e+00, -5.4327e-01,  1.7883e-01, -6.0633e-01],\n",
      "        [-4.1206e-01, -2.1665e-01, -9.6700e-01,  3.9395e-01, -4.4313e-01,\n",
      "          2.2041e+00, -7.1857e-01,  5.0685e-01, -9.6154e-01,  3.3442e-01],\n",
      "        [ 1.6440e-01, -1.7980e+00,  7.1061e-01,  7.9235e-01, -2.7175e-01,\n",
      "          8.1042e-01, -2.4518e-01, -1.0298e+00,  1.6529e+00,  2.0553e-01],\n",
      "        [ 3.1712e-01,  1.1382e-01,  1.3939e+00, -6.0567e-02, -5.0146e-01,\n",
      "          6.6686e-01,  2.0019e-01, -1.2419e+00,  5.4493e-01, -9.2382e-01],\n",
      "        [-2.6601e-01, -1.7880e+00,  1.4289e+00,  4.9100e-01, -4.2047e-01,\n",
      "         -1.5064e+00,  9.9075e-01,  2.7917e-01,  9.6519e-01, -4.6704e-01],\n",
      "        [-2.1881e+00, -1.4632e+00, -7.6852e-03, -9.0091e-01,  9.6392e-01,\n",
      "         -6.6023e-01, -8.7636e-01,  1.0746e+00,  7.6695e-01, -1.0569e+00],\n",
      "        [-1.2541e-01, -4.7280e-01,  8.3661e-01,  1.2972e+00,  4.6175e-01,\n",
      "         -2.5562e-01, -1.9006e+00, -1.3382e-01, -3.2966e-02, -1.6365e+00],\n",
      "        [-9.4210e-02,  8.9891e-01,  6.8220e-01,  2.1793e+00,  1.9390e-01,\n",
      "          1.3029e-01, -8.7606e-01, -5.1043e-01,  2.0598e-01, -9.7424e-01],\n",
      "        [ 1.1513e-01,  1.0785e-01,  2.6838e-01,  1.5375e+00,  5.6711e-01,\n",
      "          3.0644e-01, -1.0015e+00, -2.6282e+00,  5.9969e-01, -1.5323e+00],\n",
      "        [-9.9550e-01, -4.5153e-01, -1.6000e-01, -1.3856e+00,  2.5138e+00,\n",
      "          1.0641e-01,  8.2802e-01,  6.3697e-01, -1.0450e-01,  1.7327e+00],\n",
      "        [ 1.4766e+00, -1.1240e+00,  1.0344e+00,  1.1202e+00,  1.7390e-01,\n",
      "         -6.4287e-01,  3.1597e-01,  1.2734e+00,  1.5246e+00, -4.3866e-01],\n",
      "        [ 4.0019e-01,  2.7490e+00, -7.9650e-01, -5.8511e-01, -8.5939e-02,\n",
      "         -1.1488e+00, -1.4030e+00, -4.3047e-01, -1.0312e+00,  6.9982e-02],\n",
      "        [-1.6757e-02,  1.2384e+00, -2.4300e-01, -8.2466e-02,  6.0966e-01,\n",
      "         -2.3387e-02,  1.2120e+00, -7.1071e-01,  4.6943e-01, -1.4536e+00],\n",
      "        [ 6.9003e-01,  1.4926e+00,  1.2419e+00,  1.3069e+00, -1.2609e-01,\n",
      "         -9.2701e-01, -1.3008e+00, -6.0098e-02, -2.5513e+00,  1.1149e+00],\n",
      "        [-1.0850e+00,  2.0708e-01, -1.1533e+00,  1.8157e-01,  5.1177e-01,\n",
      "          8.5300e-01,  7.8226e-01, -1.5163e-01,  1.1285e-02,  9.3665e-01],\n",
      "        [ 9.4623e-01,  5.4059e-01, -1.2863e+00, -5.2160e-02, -8.5321e-01,\n",
      "         -3.9605e-01,  1.1200e+00,  9.6894e-01, -3.1673e-01,  6.6896e-01],\n",
      "        [-9.9333e-01, -8.3312e-01,  1.8410e-01, -1.1112e+00,  7.1690e-01,\n",
      "         -4.0078e-01, -1.3875e+00, -1.3579e+00, -1.1559e-01, -1.2751e-01],\n",
      "        [ 2.1048e-02,  3.9599e-01,  5.9496e-01,  2.4252e-01,  1.0529e+00,\n",
      "         -1.3458e+00, -4.9928e-01, -1.3713e+00, -1.0456e+00, -3.2123e-01],\n",
      "        [-2.3194e+00, -3.4252e-01,  2.4410e+00, -6.7097e-03,  8.2381e-01,\n",
      "         -1.6037e-01,  2.2099e-03, -5.1245e-02,  5.3906e-01, -5.4756e-01],\n",
      "        [ 4.2945e-01,  8.3863e-01,  1.4390e+00,  1.4423e+00,  4.1196e-01,\n",
      "          9.2711e-01,  6.6589e-01,  6.3155e-01,  1.1075e+00, -1.2035e+00],\n",
      "        [ 1.1153e-01, -1.2347e+00,  1.4697e-01,  3.5651e-01, -2.1751e-01,\n",
      "          6.4805e-01,  1.7712e-01, -4.1914e-01,  1.4334e+00, -4.6988e-01],\n",
      "        [-7.4614e-01,  4.8930e-01, -1.2149e+00,  1.0506e+00, -1.3417e-01,\n",
      "          1.4917e-01,  2.7066e-01, -1.2254e+00, -3.5914e-01,  4.3546e-01],\n",
      "        [-1.1074e-02,  3.9325e-01, -5.6048e-01, -1.0365e+00, -1.5314e+00,\n",
      "         -1.1386e+00,  8.5416e-01,  1.8450e+00, -1.3839e+00,  9.7838e-02],\n",
      "        [ 6.8343e-01,  6.8285e-01,  4.6981e-01, -2.8425e-01,  1.0490e+00,\n",
      "          1.8698e-01, -3.5738e-01, -6.5651e-01,  1.4492e+00,  6.8194e-01],\n",
      "        [ 3.2424e-01, -1.3713e+00, -5.9409e-01, -1.0992e+00,  2.9209e-01,\n",
      "         -1.0159e-02, -1.1085e-01,  2.0183e+00, -3.1284e-01,  3.5393e-01],\n",
      "        [ 1.1661e+00, -3.8315e-01,  6.7249e-01, -7.0591e-01,  1.8428e+00,\n",
      "          3.9837e-01, -8.0753e-01, -1.2334e-01, -2.9980e-01, -7.4522e-01],\n",
      "        [-6.2285e-01, -3.1086e+00,  7.4795e-01, -1.6781e+00, -3.7188e-01,\n",
      "          1.5964e-01, -1.3366e+00, -1.0547e+00, -2.7615e-01,  1.2707e+00],\n",
      "        [ 1.5809e+00,  3.0360e-01,  4.2393e-01,  9.8334e-01, -1.9481e+00,\n",
      "         -1.0366e+00, -1.0463e+00, -3.3434e-01, -1.2950e+00,  1.0260e+00],\n",
      "        [-2.0042e+00,  9.9147e-01,  4.9363e-02,  5.6894e-01,  1.9512e+00,\n",
      "         -4.8466e-01, -1.3629e+00, -2.5461e+00,  2.3221e-01, -1.0151e+00],\n",
      "        [-1.6813e+00, -1.3516e+00,  4.9615e-01,  1.9077e+00, -2.0229e+00,\n",
      "         -7.8436e-01,  3.1823e-02,  1.3351e-01, -3.3785e-01, -1.4863e-01],\n",
      "        [ 1.7143e+00,  9.8548e-02,  7.4066e-01, -7.9687e-01, -2.0659e+00,\n",
      "          2.2412e-01,  2.3801e+00,  3.2523e-01, -7.7244e-01, -2.0299e+00],\n",
      "        [-1.7395e-01, -1.2345e+00, -4.4642e-01,  1.0939e+00, -1.2898e+00,\n",
      "          5.0205e-01,  2.7671e-01, -2.5875e+00, -2.5364e+00, -1.0179e+00],\n",
      "        [ 1.6651e+00,  6.2807e-01,  9.0081e-01, -2.7084e+00, -2.3804e-01,\n",
      "          9.1339e-01, -1.2257e+00,  9.4362e-01, -7.9757e-01, -4.9998e-01],\n",
      "        [-7.2722e-01,  7.8685e-01, -7.3658e-02,  4.1450e-01, -6.6059e-02,\n",
      "         -3.8841e-01, -1.1167e+00,  6.9924e-01,  5.7614e-02,  5.8770e-01],\n",
      "        [-4.4814e-01, -6.6062e-01,  1.2262e-01, -4.0573e-02, -8.8021e-01,\n",
      "          6.0589e-01,  2.0273e-03, -2.5687e+00,  1.8878e+00,  7.6425e-01],\n",
      "        [-5.6902e-01,  1.4015e+00, -1.5803e+00,  3.8010e-01, -3.4443e-01,\n",
      "          8.6727e-01,  1.5856e+00, -1.6647e+00, -2.2449e-01,  3.0012e-01],\n",
      "        [-2.2795e-01,  6.7492e-01,  4.6935e-01,  1.8113e+00,  1.1174e+00,\n",
      "          5.7164e-01, -9.4372e-01, -1.2114e+00,  9.5363e-02,  8.9869e-01],\n",
      "        [-2.4002e-01,  9.4604e-01, -1.6275e+00,  6.7171e-01,  2.0026e+00,\n",
      "         -2.5294e-01,  6.2643e-01,  2.1295e+00,  9.3678e-01,  6.7118e-01],\n",
      "        [-1.4686e+00,  2.3312e-01, -8.0414e-01, -1.7097e+00,  7.8979e-01,\n",
      "          9.5225e-01,  5.4923e-01, -9.7959e-01, -6.5266e-02,  1.0764e+00],\n",
      "        [-1.6357e+00,  1.2932e+00, -5.2800e-01,  2.9845e-01,  4.2445e-01,\n",
      "          2.5743e-01, -1.1870e+00,  3.0357e-01, -4.3866e-01, -1.5027e+00],\n",
      "        [ 9.4739e-02,  7.1488e-01,  6.5420e-01,  9.6655e-01, -1.1728e+00,\n",
      "         -1.9004e-01, -2.5394e-01, -1.2083e+00, -3.3600e-01,  2.0829e-01],\n",
      "        [-1.9412e+00,  5.8507e-01,  1.0389e+00,  9.2776e-01,  6.7622e-02,\n",
      "          7.1694e-01, -2.2237e+00,  1.3517e+00, -8.1681e-01,  5.9543e-01],\n",
      "        [-1.0226e+00,  1.0676e+00, -4.2406e-01,  2.7006e+00, -1.3779e+00,\n",
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "tensor([ 0.3318, -0.7314,  0.3231, -0.1799,  1.7971,  1.4555, -0.7187,  0.3754,\n",
      "         0.1702, -1.4181,  0.2856, -1.4866, -0.2797,  0.4734,  1.1049, -0.9440,\n",
      "        -1.3829,  2.2557,  1.4220, -0.7130, -1.8209, -1.2200,  0.6525,  0.9634,\n",
      "         0.1436,  2.2090, -0.8396,  1.0320, -0.0550, -1.2999, -0.4707,  1.4646,\n",
      "         0.3402, -1.1153, -0.7463, -0.5088, -1.0608,  0.0885,  2.1814,  0.3156,\n",
      "        -0.6427,  0.8732, -0.8997, -1.5551, -0.5513, -1.0570, -0.7242,  0.3383,\n",
      "         1.1830, -2.6823,  0.5993, -1.2396, -2.0187, -0.6310, -1.4281, -0.6888,\n",
      "         0.6088,  2.5511,  1.8681,  0.5453, -0.2951, -1.3489, -2.1883, -0.3941])\n"
     ]
    }
   ],
   "source": [
    "my_dict_dataset = MyDictDataset()\n",
    "my_data_loader = DataLoader(my_dict_dataset, batch_size=64, shuffle=True)\n",
    "for batch in my_data_loader:\n",
    "    print(batch['x'])\n",
    "    print(batch['y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from torch.utils.data import TensorDataset\n",
    "x = torch.randn(10,100)\n",
    "y = torch.randn(10)\n",
    "tensor_dataset = TensorDataset(x, y)"
   ]
  }
 ],
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